Prevalence and risk predictors of childhood stunting in Bangladesh

Background The child nutritional status of a country is a potential indicator of socioeconomic development. Child malnutrition is still the leading cause of severe health and welfare problems across Bangladesh. The most prevalent form of child malnutrition, stunting, is a serious public health issue in many low and middle-income countries. This study aimed to investigate the heterogeneous effect of some child, maternal, household, and health-related predictors, along with the quantiles of the conditional distribution of Z-score for height-for-age (HAZ) of under five children in Bangladesh. Methods and materials In this study, a sample of 8,321 children under five years of age was studied from BDHS-2017-18. The chi-square test was mainly used to identify the significant predictors of the HAZ score and sequential quantile regression was used to estimate the heterogeneous effect of the significant predictors at different quantiles of the conditional HAZ distribution. Results The findings revealed that female children were significantly shorter than their male counterparts except at the 75th quantile. It was also discovered that children aged 7–47 months were disadvantaged, but children aged 48–59 months were advantaged in terms of height over children aged 6 months or younger. Moreover, children with a higher birth order had significantly lower HAZ scores than 1st birth order children. In addition, home delivery, the duration of breastfeeding, and the BCG vaccine and vitamin A received status were found to have varied significant negative associations with the HAZ score. As well, seven or fewer antenatal care visits was negatively associated with the HAZ score, but more than seven antenatal care visits was positively associated with the HAZ score. Additionally, children who lived in urban areas and whose mothers were over 18 years and either normal weight or overweight had a significant height advantage. Furthermore, parental secondary or higher education had a significant positive but varied effect across the conditional HAZ distribution, except for the mother’s education, at the 50th quantile. Children from wealthier families were also around 0.30 standard deviations (SD) taller than those from the poorest families. Religion also had a significant relationship with the conditional HAZ distribution in favor of non-Muslim children. Conclusions To enhance children’s nutritional levels, intervention measures should be designed considering the estimated heterogeneous effect of the risk factors. This would accelerate the progress towards achieving the targets of Sustainable Development Goals (SDGs) related to child and maternal health in Bangladesh by 2030.

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Background
Nutritional status is the result of aggregate connections between consumption of food, care practices and overall health conditions. Sufficient nutrition is the precondition for accomplishing sound health, quality of life, as well as national productivity. Even though complications arise due to poor nutrition affect the whole population, women as well as children have been exposed especially for the reason of their socio-economic and unique physiological characteristics. The consequences of insufficient nutrition, however, are forwarded from generation to generation, as undernourished girls have a tendency to become shorter adults and consequently are more probable to have small offspring [1]. Stunting has both short as well as long term impacts on children in direct and indirect ways, such as low birth weight, obstructing cognitive development which affect school achievement, and restricting the prospects of their life in adulthood [2].
Stunting can also affect a child's social personal development [3].
The child nutritional status of a country is performing as a potential indicator of the socioeconomic development. However, a low nutritional level is the main cause of critical health as well as welfare problems facing in Bangladesh and trying very hard to lessen child malnutrition and managed to achieve some success. The BDHS reports indicate that the rate of stunting child is declined by 12 percentage points between 2007 and 2017-18 [4]. Stunting (i.e. a low linear growth) is considered to be a considerable public health problem among children in many countries [5]. Globally, about 150.8 million of children aged under-5 years are stunted in 2017 3 [6], and nearly about 40 percent of stunted children lived in Southern Asia [7]. The serious consequences of stunting have led to the establishing of worldwide nutrition targets to lessen the prevalence of stunted children under-5 years of age by 40% before 2025 [8]. This worldwide target has since been subsequently supported by the Sustainable Development Goal 2 (SDG-2), target 2 and committed to end all kinds of malnutrition by the year 2030 and avoiding at least 1.7 million childhood deaths with the help of taking different prevention of stunting [9,10].
Furthermore, before COVID-19, it is mentioned that the current world was already off-track to accomplish the Sustainable Development Goal 2 to reduce hunger as well as all types of malnutrition by the year 2030, however, because of COVID-19 pandemic, the economic recession will faced worldwide which will be impacted hugely to meet up the global nutritional targets for stunting by 2025 specially in low and middle income countries [11,12]. About 2.6 million of children additionally will be stunted in 2022 compared due to disruptions in nutrition services as well as drops in household poverty status [13]. Fawzi et al. (2019) mention that about 7.2 million of stunting child who lived in low/middle-income countries were due to psychosocial factors [14].
However, most of these previous studies have applied either binary regression or linear regression models to explore the potential factors of child malnutrition. However, the average influence may over or underestimate the effect of the selected covariates at different points. Additional critical limitation of the binary regression model is that it treats observations equally that are above or below a threshold point and overlooks the intensity of the variations from that threshold point. As a consequence, there may possibly be a loss of information which may be relevant to intervention as well as the measures of health promotion. Though, the quantile regression (QR) model provides the robust estimates in the presence of outliers, and it not only worry with the mean as well as 4 median behaviour [56]. Besides, the QR model produced estimates that are relatively more unbiased than the estimates generated by the linear regression model when the data violate the assumption of normality [57]. Hossain & Majumder (2019) applied the quantile regression for assessing the potential correlates of the age of the mother at first birth because it is not normally distributed [58]. Also, Borooah (2005) applied QR regression for capturing the heterogeneity as well as the determinants of height-for-age in India and pointed out that access to safe water and improved hospital facilities enhance z-scores of anthropometric measurements of a child at the smallest quantiles [59]. Moreover, in this study, the coefficient of skewness of the target variable depicts that the HAZ score does not hold the normality assumption. This is the reason working behind to select the QR model for analyzing the data. Therefore, this paper attempt to investigate the correlation between demographic as well as socio-economic factors and the nutritious status of children having age less than 5 years in Bangladesh using Quantile Regression Models considering the secondary data collected from the latest BDHS-2017-18. The existing literatures indicate that a limited research is available on this vital topic with Bangladeshi data considering QR model. The Z-score of height-for-age is employed to measure child growth or stunting, and the quantile regression analysis is applied to determine the effect of demographic as well as socio-economic variables of the study children. The findings of this research will be helpful in designing the effective intervention measures targeted at preventing child malnutrition and enhancing child health status which will also be supportive of accelerating the achievement of targets set by the Sustainable Development Goals (SDGs) linked to child health status in Bangladesh by the year 2030.

Data and Variables
In this study the secondary data is obtained from a nationally representative survey called the households per cluster were carefully chosen with an equal probability-based systematic procedure from the list of households. However, data was not possible to collect from 3 EAs due to natural disaster. These three clusters were in Rajshahi (one rural cluster), Rangpur (one rural cluster), and Dhaka (one urban cluster). The sampling procedure is available on the published reports in details [4].
The child nutritional status in the survey population has compared with the Child Growth Standards recommended by the World Health Organization (WHO), which is constructed on an international sample of culturally, ethnically, and genetically distinct healthy children residing under optimum environments that are favorable to achieve a child's full genetic growth potential [4]. Among the three main anthropometric indexes for child growth, height-for-age measures the linear growth. A child is likely to be a stunted child if s/he has a height more than two standard deviations below the reference median of height for that age. As with stunting is considered severe if the child is more than three standard deviations below the reference median of height for that age [4]. The height-for-age Z-score (HAZ) is the target variable, and several child characteristics such as sex, age, duration of breastfeeding, birth order,; maternal attributes such as age, education and BMI; father's education, and attributes related to household, community along with health are the explanatory variables in this study. The selection of variables used in this study was motivated by the availability in the BDHS dataset and self-efficacy as well as guided by relevant literature.

Quantile Regression
The quantile regression (QR) model was initially introduced by Koenker and Basset in 1978, and nowadays it is extensively applied in various research areas, particularly in Statistics and Econometrics [63]. Suppose, Y be a random (response) variable having cumulative distribution and X is the p-dimensional vector of predictor variables. Then the  th conditional quantile of Y is described as where the quantile level  varies from 0 to 1.

Results
This study considered the Z-score of height-for-age as the target variable. Figure 1   18% of children were stunted (i.e. HAZ-score < -2 SD), and approximately 6% of children were severely stunted (i.e. HAZ-score < -3 SD) in Bangladesh. In the child characteristics, about 52.2% of children are male, and their prevalence rate of severe stunting is relatively less than female children. More than 13% of children have aged less than or equal to 6 months, and the rate of stunting typically increased with the child's age up to two years, however, after the second birthday of the child the rate of severe stunting decreases slightly. More than one-third of children having age less than 5 years in Bangladesh were at the first birth order, and this variable exhibited a positive association with the childhood stunting. Muslim child is slightly more stunted than their counterpart. Almost half of children are still breastfeeding (see Table 1). The findings disclose that the breastfeeding duration is negatively associated with the percentage of severely stunted child (i.e. HAZ-score < -3 SD). Within the parental characteristics, more than 7% of children mothers were young (i.e. up to 18 years old), 13.6% of children mothers were underweight and more than a half of the children mothers have had a minimum of secondary level of education. Results also reveal that while the age of mother showed a positive relationship with the occurrence of stunting, both the nutritional status (i.e. BMI) and educational status of mother and father demonstrated a negative association with the stunting rate. Furthermore, concerning the household and health characteristics, results reveal that about three-fourth of the children who lived in rural areas and a higher incidence of stunting has observed in that region compared to urban regions. Place of delivery is also a significant factor for the nutritional level of children. Moreover, by comparing the breastfeeding status of a child, like never breastfed child with the child whose breastfeeding duration is more than one year, it is seen that there is a negative effect of breastfeeding at lower quantile. Several maternal attributes like mother's age, education level and BMI have significant and highly positive impacts on HAZ-score of a child at most of the quantiles considered in this study. The increase of the mother's age improves the HAZ value. As we go from underweight mothers to mothers who has normal BMI, the HAZ score raises 0.158 and 0.276 points at 10 th and 75 th quantile respectively. Interestingly, the current location of residence is adversely linked to HAZ value at lower quantile, however, it is positively associated with upper quantiles. Besides, place of delivery, the status of receiving BCG, vitamin A and number of visit antenatal care in pregnancy period show a significant association to the HAZscore of a child. The results depict that household income is an essential factors of child health status and has a positive contribution in most of the quantile [ Table 2]. Moreover, the extent of this association also differed across the conditional distribution of HAZ score (refer to Figure 2 and Supplement Figure 1) for determining childhood malnutrition in Bangladesh.

Discussion
The prevalence of stunting and related risk factors among Bangladeshi children under the age of five are described in this research. The Z scores for height for age was used to determine the extent of stunting among children under the age of five (HAZ). Findings demonstrated that the child's age has a significant adverse association with HAZ score. The relationship varied throughout the various segments of the conditional distribution of HAZ which is consistent with the findings of another study [62,66]. Results depict that children aged 24-59 months were at higher risk for stunting than children aged 0-23. This is consistent with findings from similar studies [24,67], and may be explained by the protective effect of breastfeeding. One of the main reason working behind this is the most of the children in Bangladesh are breastfed until 24 months and breastfeeding gradually declines with child age [2,68]. The higher risk of stunting at a later age may be due to the fact that children over the age of 24 months receive less parental attention and are actively playing, particularly in unsanitary conditions where they are susceptible to diseases such as enteric infections [26].
The level of parental education was found to be a major influence in stunting in our study. Our research found that mothers with a secondary or higher level of education had significantly fewer stunted children than uneducated mothers. A similar finding was discovered for paternal education. Other studies validated the findings [2,69]. Childhood vaccines, family planning, visits to local health clinics, and vitamin A supplementation are all influenced by parental education [70]. Furthermore, it is widely accepted that better education leads to higher earnings. As a result, higher family earnings allow parents to spend more on health care and good nutrition for their children, which may explain why educated parents have a lower stunting rate [71]. The findings of quantile regression demonstrated that birth order was negatively linked with HAZ-value.
Moreover, religious status, and household's wealth index showed a positive correlation to the HAZ score in most of the cases. Data also reveal that birth order has a considerable adverse influence on the conditional distribution of HAZ-score of a child. Some of the findings of the current study having consistency with the outcome of another study [66] though they use BDHS-2014 survey data. This finding confirmed that children born at home have a higher risk of 15 malnutrition. The explanation for this could be a lack of sufficient care for children compared to the children who are born with health facilities. From health-care providers, parents received sufficient knowledge and guidance on child feeding practices and nutrition, which can be used as a measure to lessen the burden.
The household income is a contributing factor of child health status. Typically, wealthier families can ensure better medical care along with more nutritious food as well as can provide an improved and healthier living environment [72]. Children of middle-income, more affluent, and wealthiest families had a better level of HAZ scores as compared with the children come from the poorest families. Children from lower-income families were more likely to be stunted than children from higher-income families due to inadequate food consumption, a lack of basic health care, and a higher risk of infection. Furthermore, the quality of antenatal care is highly linked to one's wealth.
This study corroborated findings from previous studies in other developing nations, indicating that household economic conditions are an important factor in the nutritional status of children in developing countries [2,[73][74][75].

Conclusions
This paper has explored the influences of some selected child, maternal as well as household and health characteristics using the quantile regression method for determining child nutritional status at several points of the conditional distribution of the HAZ score. Among the predictors included in this study, the age, mother's BMI and mother's as well as father's educational status, number of antenatal care visits during pregnancy, household's wealth index were all found to be significant determinants of the Z score of height-for-age of a child. Household's wealth status was a key factor of stunting since it is directly associated with the affordability of food with high nutritional value, living in an improved and healthy environment and access to better health care services. In order to lessen the burden of malnutrition among children, the authors recommend that much more collaborative efforts by the government, NGOs and community organisations are necessary to improve the household income, especially for families in the rural area.
Along with the continuing programs for the betterment of child health status, the government of Bangladesh may need to design targeted nutritional intervention strategies with a clearer understanding of the focus group to lessen childhood stunting. Also, the easier entree to health information and inadequate health knowledge of parents, surveillance as well as assessment needs to be reviewed frequently with particular attention to vulnerable groups like children with poor maternal conditions such as mothers' with low BMI and educational status or who resided in the remote and regional areas. A healthy mother can deliver a healthy children, therefore, for enhancing the nutritional status of children, the attention of early intervention programs should be on children along with their mothers. Hence, the contributors of this paper would like to recommend that health as well as nutrition education also should be incorporated in the mass media programs and academic educational process in Bangladesh. Finally, the outcomes of this study would help practitioners and policy-makers to implement robust and cohesive programs to achieve the Sustainable Development Goals (SDGs) associated to child health in Bangladesh by 2030.

Consent to publication
Not applicable

Financial Support
This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Competing of interests
None.

Ethics approval
It is not required as the survey was approved by the Ethics Committee of the ICF Macro at Calverton in the USA and by the Ethics Committee in Bangladesh.

Data availability
This study is based on the secondary dataset. One can access the data set via the following link http://dhsprogram.com/data/available-datasets.cfm.